20 resultados para Performance Assessment

em Cambridge University Engineering Department Publications Database


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The paper describes a model for a 6-phase induction motor driven by an inverter operating in a 6-pulse (square wave) mode. The model is implemented and performance, in terms of torque, current, efficiency and pulsating torque, compared to the performance of a 3-phase motor (both sine and 6-pulse supplied). The models are verified experimentally, in particular the efficiency performance, and it is illustrated that the improvement in inverter efficiency when in 6-pulse operating mode may improve the performance of the overall system. © 2005 IEEE.

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Service-Oriented Architecture (SOA) and Web Services (WS) offer advanced flexibility and interoperability capabilities. However they imply significant performance overheads that need to be carefully considered. Supply Chain Management (SCM) and Traceability systems are an interesting domain for the use of WS technologies that are usually deemed to be too complex and unnecessary in practical applications, especially regarding security. This paper presents an externalized security architecture that uses the eXtensible Access Control Markup Language (XACML) authorization standard to enforce visibility restrictions on trace-ability data in a supply chain where multiple companies collaborate; the performance overheads are assessed by comparing 'raw' authorization implementations - Access Control Lists, Tokens, and RDF Assertions - with their XACML-equivalents. © 2012 IEEE.

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Façade design is a complex and multi-disciplinary process. One major barrier to devising optimal façade solutions is the lack of a systematic way of evaluating the true social, economic and environmental impacts of a design. Another barrier is the lack of automated design aids to assist decision-making. In this paper, we present our on-going study in developing a whole-life value based multi-objective optimisation model for high-performance façades. The principal outcome of this paper is a multi-objective optimisation model for early-stage façade design. The optimisation technique coupled with other 3rd party software and/or specially developed scripts provide façade designers with an integrated design tool of wide applicability.

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AIMS: To compare the performance of ultrasound elastography with conventional ultrasound in the assessment of axillary lymph nodes in suspected breast cancer and whether ultrasound elastography as an adjunct to conventional ultrasound can increase the sensitivity of conventional ultrasound used alone. MATERIALS AND METHODS: Fifty symptomatic women with a sonographic suspicion for breast cancer underwent ultrasound elastography of the ipsilateral axilla concurrent with conventional ultrasound being performed as part of triple assessment. Elastograms were visually scored, strain measurements calculated and node area and perimeter measurements taken. Theoretical biopsy cut points were selected. The sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) were calculated and receiver operating characteristic (ROC) analysis was performed and compared for elastograms and conventional ultrasound images with surgical histology as the reference standard. RESULTS: The mean age of the women was 57 years. Twenty-nine out of 50 of the nodes were histologically negative on surgical histology and 21 were positive. The sensitivity, specificity, PPV, and NPV for conventional ultrasound were 76, 78, 70, and 81%, respectively; 90, 86, 83, and 93%, respectively, for visual ultrasound elastography; and for strain scoring, 100, 48, 58 and 100%, respectively. There was no significant difference between any of the node measurements CONCLUSIONS: Initial experience with ultrasound elastography of axillary lymph nodes, showed that it is more sensitive than conventional ultrasound in detecting abnormal nodes in the axilla in cases of suspected breast cancer. The specificity remained acceptable and ultrasound elastography used as an adjunct to conventional ultrasound has the potential to improve the performance of conventional ultrasound alone.

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This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.

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This paper presents an assessment of the performance of an embedded propulsion system in the presence of distortion associated with boundary layer ingestion. For fan pressure ratios of interest for civil transports, the benefits of boundary layer ingestion are shown to be very sensitive to the magnitude of fan and duct losses. The distortion transfer across the fan, basically the comparison of the stagnation pressure non-uniformity downstream of the fan to that upstream of the fan, has a major role in determining the impact of boundary layer ingestion on overall fuel burn. This, in turn, puts requirements on the fidelity with which one needs to assess the distortion transfer, and thus the type of models that need to be used in such assessment. For the three-dimensional distortions associated with fuselage boundary layers ingested into a subsonic diffusing inlet, it is found that boundary layer ingestion can provide decreases in fuel burn of several per cent. It is also shown that a promising avenue for mitigating the risks (aerodynamic as well as aeromechanical) in boundary layer ingestion is to mix out the flow before it reaches the engine face.

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An assessment of the underwater blast resistance of sandwich beams with a prismatic Y-truss core is presented, utilizing three-dimensional finite element calculations. Results show a significant performance benefit for sandwich construction when compared to a monolithic plate of the same mass when the sandwich core combines high shear strength with low compressive strength.

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Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

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Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.